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autotrain-BerTweet-749522913
js3078/autotrain-BerTweet-749522913
autotrain-BerTweet-749522913 is a text classification model from js3078. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Multi-class Classification - Model ID: 749522913 - CO2 Emissions (in grams): 4.093939667345746
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Apr 16, 2022
- Updated
- Apr 16, 2022
- SHA
- b6f6a19d
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Datasets
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 749522913
- CO2 Emissions (in grams): 4.093939667345746
Validation Metrics
- Loss: 0.6473096609115601
- Accuracy: 0.75
- Macro F1: 0.7506205181665155
- Micro F1: 0.75
- Weighted F1: 0.7506205181665155
- Macro Precision: 0.7555096418732782
- Micro Precision: 0.75
- Weighted Precision: 0.7555096418732782
- Macro Recall: 0.75
- Micro Recall: 0.75
- Weighted Recall: 0.75
Usage
You can use cURL to access this model:
$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/js3078/autotrain-BerTweet-749522913
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("js3078/autotrain-BerTweet-749522913", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("js3078/autotrain-BerTweet-749522913", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- unk
- Created
- Apr 16, 2022
- Updated
- Apr 16, 2022